name: Build and Test on: pull_request: branches: [ main ] push: branches: [ main ] workflow_dispatch: # Ensure that only a single job or workflow using the same # concurrency group will run at a time. This would cancel # any in-progress jobs in the same github workflow and github # ref (e.g. refs/heads/main or refs/pull//merge). concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: true # Provisioned Jobs: # ubuntu - x86_64 - llvm in-tree - pytorch binary - build+test # most used dev flow and fastest signal # ubuntu - x86_64 - llvm out-of-tree - pytorch source - build+test # most elaborate build # macos - arm64 - llvm in-tree - pytorch binary - build only # cross compile, can't test arm64 jobs: build-test: strategy: fail-fast: true matrix: os-arch: [ubuntu-x86_64, macos-arm64] llvm-build: [in-tree, out-of-tree] torch-binary: [ON, OFF] exclude: # Exclude llvm in-tree and pytorch source - llvm-build: in-tree torch-binary: OFF # Exclude llvm out-of-tree and pytorch binary - llvm-build: out-of-tree torch-binary: ON # Exclude macos-arm64 and llvm out-of-tree altogether - os-arch: macos-arm64 llvm-build: out-of-tree include: # Specify OS versions - os-arch: ubuntu-x86_64 os: ubuntu-22.04 - os-arch: macos-arm64 os: macos-12 runs-on: ${{ matrix.os }} steps: - name: Checkout torch-mlir uses: actions/checkout@v2 with: submodules: 'true' - name: Setup ccache uses: ./.github/actions/setup-build with: cache-suffix: ${{ matrix.os-arch }}-${{ matrix.llvm-build }}-${{ matrix.torch-binary }} - name: Configure os-arch='ubuntu-x86_64' llvm-build='in-tree' torch-binary='${{ matrix.torch-binary }}' # Fastest build, most used dev flow if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }} run: | cmake -GNinja -Bbuild \ -DCMAKE_BUILD_TYPE=Release \ -DCMAKE_C_COMPILER=clang \ -DCMAKE_CXX_COMPILER=clang++ \ -DCMAKE_C_COMPILER_LAUNCHER=ccache \ -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ -DCMAKE_LINKER=lld \ -DLLVM_ENABLE_ASSERTIONS=ON \ -DLLVM_ENABLE_PROJECTS=mlir \ -DLLVM_EXTERNAL_PROJECTS="torch-mlir;torch-mlir-dialects" \ -DLLVM_EXTERNAL_TORCH_MLIR_SOURCE_DIR="$GITHUB_WORKSPACE" \ -DLLVM_EXTERNAL_TORCH_MLIR_DIALECTS_SOURCE_DIR="${GITHUB_WORKSPACE}/externals/llvm-external-projects/torch-mlir-dialects" \ -DLLVM_TARGETS_TO_BUILD=host \ -DMLIR_ENABLE_BINDINGS_PYTHON=ON \ -DTORCH_MLIR_ENABLE_LTC=ON \ -DTORCH_MLIR_USE_INSTALLED_PYTORCH="${{ matrix.torch-binary }}" \ -DPython3_EXECUTABLE="$(which python)" \ $GITHUB_WORKSPACE/externals/llvm-project/llvm - name: Configure os-arch='ubuntu-x86_64' llvm-build='out-of-tree' torch-binary='${{ matrix.torch-binary }}' # Most elaborate build, but cached if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'out-of-tree' }} run: | cmake -GNinja -Bllvm-build \ -DCMAKE_BUILD_TYPE=Release \ -DCMAKE_C_COMPILER=clang \ -DCMAKE_CXX_COMPILER=clang++ \ -DCMAKE_C_COMPILER_LAUNCHER=ccache \ -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ -DCMAKE_LINKER=lld \ -DLLVM_ENABLE_ASSERTIONS=ON \ -DLLVM_ENABLE_PROJECTS=mlir \ -DLLVM_TARGETS_TO_BUILD=host \ -DMLIR_ENABLE_BINDINGS_PYTHON=ON \ -DPython3_EXECUTABLE="$(which python)" \ $GITHUB_WORKSPACE/externals/llvm-project/llvm cmake --build llvm-build cmake -GNinja -Bbuild \ -DCMAKE_C_COMPILER=clang \ -DCMAKE_CXX_COMPILER=clang++ \ -DCMAKE_C_COMPILER_LAUNCHER=ccache \ -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ -DCMAKE_LINKER=lld \ -DLLVM_DIR="$GITHUB_WORKSPACE/llvm-build/lib/cmake/llvm/" \ -DMLIR_DIR="$GITHUB_WORKSPACE/llvm-build/lib/cmake/mlir/" \ -DMLIR_ENABLE_BINDINGS_PYTHON=OFF \ -DTORCH_MLIR_USE_INSTALLED_PYTORCH="${{ matrix.torch-binary }}" \ -DPython3_EXECUTABLE="$(which python)" \ $GITHUB_WORKSPACE - name: Configure os-arch='macos-arm64' llvm-build='in-tree' torch-binary='${{ matrix.torch-binary }}' # cross compile, can't test arm64 if: ${{ matrix.os-arch == 'macos-arm64' && matrix.llvm-build == 'in-tree' }} run: | cmake -GNinja -Bbuild_arm64 \ -DCMAKE_BUILD_TYPE=Release \ -DCMAKE_C_COMPILER=clang \ -DCMAKE_CXX_COMPILER=clang++ \ -DCMAKE_C_COMPILER_LAUNCHER=ccache \ -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ -DCMAKE_LINKER=lld \ -DCMAKE_OSX_ARCHITECTURES=arm64 \ -DLLVM_ENABLE_ASSERTIONS=ON \ -DLLVM_ENABLE_PROJECTS=mlir \ -DLLVM_EXTERNAL_PROJECTS="torch-mlir;torch-mlir-dialects" \ -DLLVM_EXTERNAL_TORCH_MLIR_SOURCE_DIR="$GITHUB_WORKSPACE" \ -DLLVM_EXTERNAL_TORCH_MLIR_DIALECTS_SOURCE_DIR="${GITHUB_WORKSPACE}/externals/llvm-external-projects/torch-mlir-dialects" \ -DLLVM_TARGETS_TO_BUILD=AArch64 \ -DLLVM_USE_HOST_TOOLS=ON \ -DLLVM_ENABLE_ZSTD=OFF \ -DMLIR_ENABLE_BINDINGS_PYTHON=ON \ -DTORCH_MLIR_ENABLE_MHLO=OFF \ -DTORCH_MLIR_USE_INSTALLED_PYTORCH="${{ matrix.torch-binary }}" \ -DMACOSX_DEPLOYMENT_TARGET=12.0 \ -DPython3_EXECUTABLE="$(which python)" \ $GITHUB_WORKSPACE/externals/llvm-project/llvm - name: Build torch-mlir if: ${{ matrix.os-arch == 'ubuntu-x86_64' }} run: | cmake --build build - name: Build torch-mlir (cross-compile) if: ${{ matrix.os-arch == 'macos-arm64' }} run: | cmake --build build_arm64 - name: Run torch-mlir unit tests if: ${{ matrix.os-arch == 'ubuntu-x86_64' }} run: | cmake --build build --target check-torch-mlir-all - name: Run refbackend e2e integration tests if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }} run: | export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir" python -m e2e_testing.torchscript.main --config=refbackend -v - name: Run eager_mode e2e integration tests if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }} run: | export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir" python -m e2e_testing.torchscript.main --config=eager_mode -v - name: Run tosa e2e integration tests if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }} run: | export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir" python -m e2e_testing.torchscript.main --config=tosa -v - name: Run lazy_tensor_core e2e integration tests if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }} run: | export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir" python -m e2e_testing.torchscript.main --config=lazy_tensor_core -v